What Predicts Successful Use and Completion of an Adaptive Mathematics Software Intervention?

• In Event: 33.076 - Teaching and Learning Mathematics With Technology

Abstract

This study analyzes patterns and predictors in detailed performance data collected internally by adaptive web-based software designed to improve middle school students’ structural understanding of and fluency with fractions. Our sample consists of 764 sixth graders in 29 Philadelphia public schools who participated in the first cohort of a larger randomized controlled trial. We use measures of active learning time and initial accuracy with the software to define indicators and norms that teachers can use to actively manage students’ use of the software. These types of norms are crucial in helping teachers implement the intended software intervention effectively for children, regardless of their prior knowledge or initial accuracy with the software.

Authors

• Jill Bowdon, American Institutes for Research

• Christine M. Massey, University of Pennsylvania

• Jennifer Diane Kregor, University of Pennsylvania

• Janie Scull, University of Pennsylvania